Muhammad Imam | FOG computing | Best Researcher Award

Assist Prof Dr. Muhammad Imam | FOG computing | Best Researcher Award

Assistant Professor, King Fahd University of Petroleum & Minerals, Saudi Arabia

Dr. Muhammad Y. Imam is a distinguished Cybersecurity Leader and Consultant with over 20 years of experience in the fields of cybersecurity, cryptography, and blockchain. He has a proven track record of combining entrepreneurship with technical expertise, excelling in problem-solving and innovative solutions. Currently an Assistant Professor at KFUPM, Dr. Imam is committed to enhancing cybersecurity education and practice in the region. 🌐🔐

Publication Profile

ORCID

 

Strengths for the Award

  1. Extensive Expertise in Cybersecurity: Dr. Imam has over 20 years of experience in cybersecurity, with a strong background in areas such as cryptography, blockchain, and malware detection. This extensive knowledge positions him as a leader in the field.
  2. Innovative Research Contributions: His PhD research focused on botnet mitigation techniques, showcasing his ability to develop novel solutions for complex problems. This work is crucial in addressing emerging threats in cybersecurity.
  3. Academic and Administrative Leadership: As an Assistant Professor at KFUPM and former Director of the Business Incubator, Dr. Imam demonstrates strong leadership skills. He has been actively involved in various committees, contributing to policy-making and curriculum development.
  4. Impactful Publications: With a range of publications in reputable journals, including works on secure PIN-entry methods and malware classification, Dr. Imam has made significant contributions to academic literature in cybersecurity.
  5. Strong Network and Collaboration: His involvement with various organizations, such as ARAMCO and Saudi Airlines, highlights his ability to bridge academia and industry, fostering collaborations that enhance research impact.
  6. Commitment to Education: Dr. Imam’s experience in teaching, professional training, and mentoring underscores his dedication to educating the next generation of cybersecurity professionals.

Areas for Improvement

  1. Broader Research Focus: While Dr. Imam has a strong background in cybersecurity, expanding his research to include emerging fields like artificial intelligence and machine learning in security applications could further enhance his profile.
  2. Enhanced Public Engagement: Increasing participation in public forums or conferences to share his research findings could amplify his impact and visibility within the global cybersecurity community.
  3. Collaboration with Diverse Disciplines: Engaging with researchers from different fields, such as sociology or behavioral science, could provide a more holistic approach to understanding cybersecurity issues, particularly in user behavior and security practices.
  4. Grant Acquisition: Actively pursuing more research grants and funding opportunities could help elevate his projects and provide resources for broader research initiatives.

Education

Dr. Imam earned his Ph.D. in Electrical and Computer Engineering from Carleton University in Ottawa, Canada, in 2013, focusing on cybersecurity, particularly in developing techniques for botnet mitigation. He also holds a Master’s degree from KFUPM, where he graduated in June 2004, and a Bachelor’s degree from the same institution, completed in May 2000. 🎓📚

Experience

Since September 2013, Dr. Imam has served as an Assistant Professor in the Computer Engineering Department at KFUPM, where he is involved in teaching, professional training, and research projects with industry partners. He previously directed the Business Incubator at KFUPM’s Entrepreneurship Institute, managing incubation and acceleration programs to support new startups. His leadership extends to various committees, including chairing the Cybersecurity Committee at KFUPM since January 2023. 👨‍🏫💼

Research Focus

Dr. Imam’s research interests are centered around cybersecurity, focusing on cryptography, network security, and malware detection. His innovative work includes developing advanced solutions for data privacy and risk management, addressing contemporary challenges in information security. 🔍💻

Awards and Honors

Throughout his career, Dr. Imam has been recognized for his contributions to cybersecurity education and practice, receiving accolades for his research and leadership in various academic and professional capacities. He has also been involved in multiple initiatives to improve cybersecurity awareness and education in Saudi Arabia and beyond. 🏅👏

Publications

F. Binbeshr, L. Y. Por, M. L. M. Kiah, A. A. Zaidan, and M. Imam, “Secure PIN-Entry Method Using One-Time PIN (OTP),” IEEE Access, vol. 11, pp. 18121-18133, 2023.

Al Mousa, M. Al Qomri, and M. Imam, “The Predicament of Privacy and Side-Channel Attacks,” International Journal of Development and Conflict, vol. 12, no. 2, pp. 182–191, 2022.

L. Ghouti and M. Imam, “Malware Classification Using Compact Image Features and Multiclass Support Vector Machines,” IET Information Security, vol. 14, no. 4, pp. 419–429, 2020.

M. Mahmoud, M. Nir, and A. Matrawy, “A Survey on Botnet Architectures, Detection and Defences,” International Journal of Network Security, vol. 17, no. 3, pp. 272–289, 2015.

M. Mahmoud, S. Chiasson, and A. Matrawy, “Does Context Influence Responses to Firewall Warnings?,” 2012 eCrime Researchers Summit, Las Croabas, PR, USA, 2012, pp. 1-10.

Conclusion

Dr. Muhammad Y. Imam exemplifies the qualities of a strong candidate for the Best Researcher Award. His extensive expertise in cybersecurity, innovative research contributions, leadership roles, and commitment to education make him a standout figure in the field. Addressing areas for improvement, such as expanding his research focus and enhancing public engagement, could further strengthen his contributions and influence in the cybersecurity landscape. Given these strengths and opportunities, Dr. Imam is well-positioned to receive recognition for his impactful work and leadership in the realm of cybersecurity.

Isabel de la Torre | Computer Science | Women Researcher Award

Prof Dr. Isabel de la Torre | Computer Science | Women Researcher Award

Catedrática, Universidad de Valladolid, Spain

Isabel de la Torre Díez, born in 1979 in Zamora, Spain, is a renowned Full Professor at the University of Valladolid. She received her M.S. and Ph.D. degrees in Telecommunication Engineering from the same university in 2003 and 2010, respectively. Isabel’s expertise lies in telemedicine, e-health, m-health, and related fields. She has authored over 250 papers and played a significant role in numerous research projects. Isabel leads the GTe Research Group and is a key figure in the field of telemedicine and e-health. 🌐👩‍🏫

Publication Profile

 

Strengths for the Award

  1. Significant Research Contributions: Isabel de la Torre Díez has published over 250 papers in SCI journals, peer-reviewed conferences, and books. This extensive publication record highlights her impactful research in telemedicine, e-health, and related fields.
  2. Leadership and Innovation: She leads the GTe Research Group at the University of Valladolid and has been involved in creating and coordinating innovative software. Her leadership in advancing telemedicine and e-health applications demonstrates her commitment to improving healthcare through technology.
  3. Research Impact and Recognition: She has been involved in over 100 international conference program committees and has participated in numerous funded research projects. Her involvement as a reviewer for well-known SCI journals further underscores her expertise and influence in her field.
  4. Research and Teaching Excellence: With two research sexenios, she has demonstrated consistent research excellence. Her role in guiding doctoral theses and her contributions to high-impact journals and conferences reflect her high standing in the academic community.
  5. International Collaboration: Her postdoctoral research experiences in Portugal, Spain, and France highlight her international collaboration and mobility, enhancing her global research network and exposure.

Areas for Improvement

  1. Broader Recognition: While her research is extensive, further highlighting any awards or recognitions she has received could strengthen her application. Emphasizing awards or honors related to her research could enhance her candidacy.
  2. Diversity of Research Interests: While her focus is on telemedicine and e-health, demonstrating how her research contributes to a broader range of applications or interdisciplinary areas might strengthen her profile.
  3. Detailed Impact Metrics: Providing specific metrics, such as citation counts, h-index, and impact factors of the journals where she has published, could offer a clearer picture of her research impact.

Conclusion

Isabel de la Torre Díez is a highly qualified candidate for the Research for Women Researcher Award. Her extensive research contributions, leadership in innovative projects, and active participation in international research communities position her as a leading figure in her field. Enhancing her application with additional recognitions and detailed impact metrics could further bolster her candidacy. Overall, her achievements and ongoing contributions to the field of telemedicine and e-health make her a strong contender for the award.

Education 🎓

Isabel de la Torre Díez earned her M.S. and Ph.D. degrees in Telecommunication Engineering from the University of Valladolid, Spain, in 2003 and 2010, respectively. Her education laid a strong foundation for her prolific career in telemedicine and e-health. 🏫📜

Experience 👩‍💼

Isabel de la Torre Díez is a Full Professor in the Department of Signal Theory and Communications and Telematics Engineering at the University of Valladolid. She has authored over 250 papers and coauthored 16 registered innovative software. Isabel has been involved in more than 100 international conference program committees and has participated in 44 funded research projects. She is also a reviewer for renowned journals like the International Journal of Medical Informatics. 🏫📚

Research Focus 🔬

Isabel’s research focuses on the development and evaluation of telemedicine applications, e-health, m-health, EHRs (Electronic Health Records), machine and deep learning, privacy and security, biosensors, QoS (Quality of Service), and QoE (Quality of Experience) in the health field. She has significantly contributed to these areas, particularly in telepsychiatry, teleophthalmology, and telecardiology. 🧠💻

Awards and Honors 🏆

Isabel de la Torre Díez has received numerous accolades throughout her career. She has two research sexenios and coordinates the GTe Research Group and the GIR “Society of Information” group. She has also been recognized for her contributions as a reviewer for prestigious journals and her leadership in various research projects and collaborations. 🌟🏅

Publications 📄

  1. Novel model to authenticate role-based medical users for blockchain-based IoMT devices
    PLOS ONE
    2024-07-10
    DOI: 10.1371/journal.pone.0304774
  2. A Digital Mental Health Approach for Supporting Suicide Prevention: A Qualitative Study
    International Journal of Mental Health and Addiction
    2024-06-21
    DOI: 10.1007/s11469-024-01347-4
  3. A deep learning approach for Named Entity Recognition in Urdu language
    PLoS ONE
    2024
    DOI: 10.1371/journal.pone.0300725
    Cited by 1 article
  4. A Detectability Analysis of Retinitis Pigmentosa Using Novel SE-ResNet Based Deep Learning Model and Color Fundus Images
    IEEE Access
    2024
    DOI: 10.1109/ACCESS.2024.3367977
    Cited by 1 article

 

Tidjani Négadi | Computer Science | Best Researcher Award

Dr. Tidjani Négadi | Computer Science | Best Researcher Award

recently retired, Physics Department, Faculty of Exactand Applied Science, University Oran 1 Ahmed Ben Bella, Oran 31100, Algeria,

📅 Born on January 26, 1950, in Tlemcen, Algeria, Tidjani Négadi is a distinguished Maître de Conférence at the Physics Department, Faculty of Exact and Applied Science, University Oran 1 Ahmed Ben Bella, Oran, Algeria. With a profound interest in theoretical and mathematical biology, Négadi has significantly contributed to various fields, especially in exploring the connections between physics and biological systems.

Profile

Google Scholar

Education

🎓 Tidjani Négadi earned his Doctorat de 3ème Cycle in Nuclear Physics in 1976 and a Doctorat d’Etat Es-Science Physiques in Theoretical Physics in 1988, both from the Institut de Physique Nucléaire IN2P3, Université Claude Bernard Lyon-I, France. His extensive education laid the foundation for his interdisciplinary research spanning nuclear physics, theoretical physics, and mathematical biology.

Experience

💼 Négadi’s academic journey began in 1976, teaching Quantum Mechanics and its applications until 1989. He later taught Atomic and Molecular Physics, and Group Theory until 2002, after which he focused solely on research, particularly in Mathematical Biology. His teaching portfolio also includes Special Relativity, Astronomy, and Astrophysics from 2015 to 2018. His editorial roles and contributions to esteemed journals and conferences highlight his expertise and dedication to advancing scientific knowledge.

Research Interests

🔬 Négadi’s research interests are vast and interdisciplinary, focusing on the mathematical modeling of biological systems, particularly the genetic code. He has explored the symmetries in the genetic code, the use of Fibonacci and Lucas numbers, and the application of quantum-like approaches to biological systems. His work bridges the gap between physics and biology, offering novel insights into genetic information and its underlying structures.

Awards

🏆 Tidjani Négadi’s contributions to science have been recognized with several prestigious awards and honors. He has served as a member of the Executive Board and Advisory Board of the International Symmetry Association (ISA) and the Advisory and Editorial Board of NeuroQuantology. His role as a guest editor for various special issues in prominent journals showcases his leadership in the scientific community.

Publications

1976: Lifetimes of levels in 64Zn from Doppler shift measurements via 61Ni(a,n) 64Zn reaction, Phys. Rev. C13, cited by 10 articles.

1983: On the connection between the hydrogen atom, and the harmonic oscillator, Lett. Nuovo Cimento, cited by 15 articles.

1983: On the connection between the hydrogen atom, and the harmonic oscillator: the continuum case, J. Phys. A16, cited by 12 articles.

1984: Connection between the hydrogen atom, and the harmonic oscillator: the zero-energy case, Phys. Rev. A29, cited by 9 articles.

1984: Hydrogen atom in a uniform electromagnetic field as an anharmonic oscillator, Lett. Nuovo Cimento, cited by 7 articles.

HaiTian Chen | Computer Science | Best Researcher Award

Ms. HaiTian Chen | Computer Science | Best Researcher Award

College of Science, North China University of Science and Technology, China

Chen HaiTian is a dedicated researcher in the field of Cyberspace Security from China. Born in December 1998, Chen has made significant strides in federated learning, privacy preservation, and cybersecurity. His contributions span multiple peer-reviewed journals and patents, showcasing his commitment to advancing technology and safeguarding digital spaces.

Profile

ORCID

 

Education

Chen HaiTian holds a major in Cyberspace Security, demonstrating his expertise and focus in this critical area of study. His academic background has equipped him with the skills and knowledge necessary to tackle complex cybersecurity challenges and contribute to innovative solutions in the field. 🎓

Research Interests

Chen HaiTian’s research interests focus on federated learning, privacy preservation, and cybersecurity. He is particularly interested in developing robust aggregation techniques to defend against poisoning attacks in federated learning and exploring personalized fair split learning for resource-constrained Internet of Things (IoT). 🔍

Awards

Chen HaiTian has received recognition for his contributions to software development, including the Huali Academy Backstage Management System V1.0 and the DC Early Warning System V1.0. His work has been registered with computer software registration numbers, showcasing his achievements in developing innovative solutions for network management and security. 🏆

Publications

Chen, H.; Chen, X.; Peng, L. (2023). FLRAM: Robust Aggregation Technique for Defense Against Byzantine Poisoning Attacks in Federated Learning. Electronics. Cited by Electronics.

Chen, H.; Chen, X.; Peng, L. (2024). Personalized Fair Split Learning for Resource-Constrained Internet of Things. Sensors, 24, 88. Cited by Sensors.

Chen, H., Chen, X., Ma R., et al. (2024). A federated learning privacy preserving approach for remote sensing data. Computer Applications. Cited by Computer Applications.

Chen, H., Chen, X. (2023). A Robust Aggregation Technique for Poisoning Attack Defense in Federated Learning. Cited by Journal.

Xu C., Zhang S., Chen H., et al. (2024). A federated learning approach based on adaptive differential privacy and customer selection optimization. Computer Applications. Cited by Computer Applications.

Peng L., Zhang S., Chen H., et al. (2023). Clustered federated learning based on improved CFSFDP algorithm. Journal of North China University of Science and Technology (Natural Science Edition). Cited by NCUST.

Qiang Li | Computer Science | Best Researcher Award

Mr. Qiang Li | Computer Science | Best Researcher Award

Lecturer, Qingdao University, China

Dr. Li Qiang is an experienced lecturer in computer science with a PhD in Engineering. He specializes in high-performance computing and has a strong background in both teaching and research. Committed to fostering academic excellence and technological innovation, Dr. Li has been a dedicated educator and researcher at Qingdao University since 2015.

Profile

ORCID

 

Education 🎓

PhD in Engineering: University of the Chinese Academy of Sciences, Computer Network Information Center (2010-2014), Advisor: Lu Zhonghua. Master’s in Information Science and Engineering: Shandong University of Science and Technology (2007-2010), Advisor: Zhao Maoxian. Bachelor’s in Education: Qingdao University (2003-2007).

Experience 👨‍🏫

Lecturer at Qingdao University, School of Computer Science and Technology (January 2015-Present). Teaching undergraduate and graduate courses in computer science. Supervising student research projects and theses. Conducting research in high-performance computing. Published 12 research papers in journals and conferences. Granted 2 patents.

Research Interests 🔬

Dr. Li Qiang’s research interests lie in high-performance computing, particularly in the optimization and parallel implementation of numerical simulations and the development of new computational frameworks. His work focuses on enhancing computational efficiency and scalability in large-scale scientific computations.

Awards 🏆

Dr. Li Qiang has been recognized for his contributions to the field of high-performance computing through multiple publications and patents. His innovative work has led to advancements in computational methods and has garnered attention in the academic community.

Publications 📄

Optimization Research of Heterogeneous 2D-Parallel Lattice Boltzmann Method Based on Deep Computing Unit. Appl. Sci. 2024, 14, 6078.

Heterogeneous Parallel Implementation of Large-Scale Numerical Simulation of Saint-Venant Equations. Appl. Sci. 2022, 12, 5671. Cited by 6

The Study of Parallelization of SWAT Hydrology Cycle. The 32nd ACM International Conference on Supercomputing, Beijing, 2018. [Cited by 3]

A New Parallel Framework of Distributed SWAT Calibration. Journal of Arid Land, 2015, 7(1): 122-131. [Cited by 7]

Parallel Simulation of High-Dimensional American Option Pricing Based on CPU VS MIC. Concurrency and Computation: Practice and Experience, 2014, 27(5): 1110-1121. [Cited by 5]